Even if you haven’t warmed to the idea yet; its status, adoption and allure is spreading rapidly.

Its brand is both evocative and provocative – albeit in entirely separate ways, for equally different audiences.

And, if you fail to embrace this phenomenon, you might consign yourself as an outcast.

Socially, it’s a lonely but fairly incidental tale. In business, it might mean the beginning of the end.

However, as with tweenage affinity for teenage twits One Direction, the key to unraveling the mystic around Big Data analytics – and identifying its usefulness or appeal to your particular situation – resides in your ability to avoid the superfluous fever and fervor. Carefully dissecting the entity and its prevalence as a whole, and assessing how each factor or potential benefit might relate to you, is essential.

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But what is this numinous and illusive term, nebulously labeled ‘Big Data’?

Defining Big Data

At the most basic level, Big Data comprises the three V’s: Volume (total amount of data), Variety (different data types – structured and unstructured) and Velocity (the speed with which you are acquiring, processing and querying data).

Goal oriented and actionable intelligence But take note; volume should not be thought about as the total amount of data you can potentially, or do currently, collect. It’s really the amount of data you need to collect to support a specific reporting and analytics objective, which in turn supports a clearly defined business goal. This is true volume. After all, what’s the point in collecting data for the sake of it? The value in Big Data doesn’t dwell in the data itself, or in its increasing volume. Value is achieved through the ability to extract and act on insights derived from that data, for direct or indirect (usually financial) gain.

As Colin White, President and Founder of BI Research, said in a recent interview in relation to Big Data, “It’s time to move from Big Data management to Big Data analytics – it’s what you do with the data that matters.”

Likewise, requirements pertaining to data variety and velocity need to be assessed with specific business outcomes in mind.

It’s not the size; it’s how you use it Similarly, Big Data – and data volume – is a relative concept. Theoretically, a smaller organization, struggling to capture and leverage terabytes worth of data with its existing technologies, may have a legitimately equivalent Big Data opportunity as compared to a large business looking to exploit many petabytes worth of data.

So, it’s not about the size; it’s about how you use it, and whether you have the right tools (for your specific situation) to help you utilize it effectively.

Some would argue that, to a certain degree, Big Data has always been an omnipresent aspect of our lives. The only difference now, is that the technology necessary to capture that information – and hopefully extract value from it – is readily available at a financially viable price point.

Whilst this argument is vastly true, the emergence of myriad new data sources and types (from various geospatial, social media and mobile sources), in conjunction with the growth of existing sources (think about the proliferation of Web traffic, e-mail, the growing sophistication of computer tracking of supply chain processes and customers), has also had notable contributory consequences.

And whilst it’s important to contextualize the growth of data, it’s also equally important not to understate its growth; both in terms of total volume and acceleration.

Market research firm IDC estimated that the total volume of data created and replicated in 2009 was enough to fill a stack of DVDs reaching to the moon and back. They predict this volume to grow 44 times over by 2020. IDC suggests that the world’s data has grown almost nine times in the past five years. IBM estimates that 90 percent of the data in the world today was created in the last two years.

So, there’s a lot of information out there, relevant to the performance of your organization, that you’re now capable of collecting. But why would you bother trying to understand that information, and make decisions based on those understandings?

Why bother with Big Data analytics?

Well, many of you are already collecting large, untapped, information resources – so you might as well accomplish something constructive with that data. A recent MIT Sloan Management Review survey of over 3,000 executives found that 60 percent of respondents collect more data than they can effectively use.

Further, harnessing Big Data provides an opportunity to understand your business operations and customers at a deeper, more granular level.

“If your organization is one of the growing number looking for deeper insight into customers and operations, then you understand that Big Data will be key,” said Director of IDC’s Asia/Pacific Business Analytics Research, Craig Stires, in a recent media statement.

“With technology barriers falling, organizations are given affordable access to infrastructure that scales up and out,” continued Stires. “It’s a great time to be mapping out how you can lead the transformation in your organization. It’s the right time to pay attention to the combination of increasing availability of experiences, end-user awareness, affordable technologies, and emerging vendor solutions. Making a critical, informed decision on your Big Data strategy today will be crucial to your organizations success and continued competitiveness tomorrow.”

Do you disagree? Maybe you think that Big Data’s just a hassle – an unnecessary burden. If that sounds like you, you might want shift your mindset on the subject. According to research firm Harris Interactive, 70 percent of organizations (and your competitors) view Big Data as a big business opportunity. Further, 70 percent those organizations already investing in Big Data initiatives expect to see a ROI within a single year. And if you’re not thinking about how to harness Big Data, you might soon find yourself in trouble, because your competitors already are. According to a new survey of 200 IT and business professionals by data integration company Informatica, the majority of organizations (70%) are already considering (27%), planning (20%), testing (7%) or running (15%) Big Data projects.

More importantly still, 84 percent of organizations actively leveraging Big Data claim that they can now make better decisions as a direct result of that investment (Avanade).

“Companies that use this type of ’data-driven decision making’ actually show higher performance,” wrote Brynjolfsson. “Working with Lorin Hitt and Heekyung Kim, I analyzed 179 large publicly traded firms and found that the ones that adopted this method are about five percent more productive and profitable than their competitors.”

“Simply put, because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved decision making and performance,” wrote Brynjolfsson.

“We believe there is a more fundamental transformation of the economy happening.

“The evidence is clear: Data-driven decisions tend to be better decisions. In sector after sector, companies that embrace this fact will pull away from their rivals. We can’t say that all the winners will be harnessing big data to transform decision-making. But the data tell us that’s the surest bet.”

McKinsey Global Institute’s assessment of the situation echoes Brynjolfsson’s, with the firm forecasting that “Analyzing large data sets – so called big data – will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus.”

So which industries stand to benefit the most from embracing the Big Data analytics revolution?

Who can benefit from Big Data analytics?

Brynjolfsson believes that organizations from across almost all industries can enhance their operations and strategic decision-making by implementing Big Data analytics programs, stating that he is now “convinced that almost no sphere of business activity will remain untouched by this movement. We’ve seen big data used in supply chain management to understand why a carmaker’s defect rates in the field suddenly increased, in customer service to continually scan and intervene in the health care practices of millions of people, in planning and forecasting to better anticipate online sales on the basis of a data set of product characteristics.”

Further, embracement of Big Data will create entirely new industries and data-centric economies. In terms of business applications, recent TDWI research has found that over 45 percent of current Big Data deployments are aimed at enhancing marketing efforts, with spending on digital marketing set to grow from $34 to $76 billion by 2016.

How can you benefit from Big Data analytics?

Organizations embracing Big Data analytics programs expect to achieve a range of benefits, according to the aforementioned Informatica study.

Improving efficiency in business operations was the number one benefit sought from Big Data operations (55%), followed by attracting and retaining customers (38%).

Survey respondents also listed the aspects of Big Data most relevant to their organization, as the management and analysis of:

Growing transaction volumes (58%)

Social media data (26%)

Mobile device data (21%)

Machine-generated data (16%)

But how do you get there?

Whilst the potential and mounting importance of capturing and analyzing growing and emerging data types – in order to achieve strategic business goals – is undeniable, understanding how to achieve the desired benefits remains difficult.

So join us for our series of Big Data & BI Best Practice Webinars to dispel the confusion, and find out how to get started with Big Data analytics today!

Lachlan James is the Communications Coordinator for Yellowfin.
Yellowfin is a global Business Intelligence software vendor headquartered and developed in Melbourne, Australia.
Yellowfin is an innovative and flexible 100 percent web-based reporting and analytics solution. For regular updates and news follow Yellowfin on Twitter (@YellowfinBI) or subscribe to our free ...

As you also mention, I think the key in this proliferating conversation around Big Data, is to ensure that the focus is shifted towards Big Data analytics, not just Big Data management. After all, the whole point of collecting more information is to synthesize understanding that can be applied to specific business outcomes.

Additionally, thanks for your note regarding the 3V’s – I quite honestly had no idea that Gartner pioneered that terminology / framework!

Thorough piece Lachlan. Enjoyed it. Good to see the "3V's Gartner identified and first published about 12 years ago are finally understood and have been broadly adopted by the industry. For proper attribution, here is the piece I wrote in 2001 first suggesting and defining these three dimensions: http://blogs.gartner.com/doug-laney/deja-vvvue-others-claiming-gartners-volume-velocity-variety-construct-for-big-data/.

Since then, Gartner has identified 12 dimensions of data management challenge and published an updated definition of Big Data that reflects (as you also suggest) the value side of Big Data equation: "Big Data are high-volume, -velocity, and/or variety information assets that require innovative forms of processing for enhanced decision support, business insights, and process optimization."

Gartner has also developed methods for quantifying the economic value of Big Data sources that companies can use to gauge investments and opportunities in information management/analytics/infosec/etc, and a data magnitude index (DMI) that can help in planning and anticipating needs for new infrastructure & architectures.